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Orthogonal Ensemble Networks for Biomedical Image Segmentation

Orthogonal Ensemble Networks for Biomedical Image Segmentation

22 May 2021
Agostina J. Larrazabal
Cesar E. Martínez
Jose Dolz
Enzo Ferrante
    UQCV
ArXivPDFHTML

Papers citing "Orthogonal Ensemble Networks for Biomedical Image Segmentation"

7 / 7 papers shown
Title
Fairness of Deep Ensembles: On the interplay between per-group task difficulty and under-representation
Fairness of Deep Ensembles: On the interplay between per-group task difficulty and under-representation
Estanislao Claucich
Sara Hooker
Diego H. Milone
Enzo Ferrante
Rodrigo Echeveste
FedML
44
0
0
24 Jan 2025
The Devil is in the Margin: Margin-based Label Smoothing for Network
  Calibration
The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration
Bingyuan Liu
Ismail Ben Ayed
Adrian Galdran
Jose Dolz
UQCV
18
65
0
30 Nov 2021
SUPER-Net: Trustworthy Medical Image Segmentation with Uncertainty
  Propagation in Encoder-Decoder Networks
SUPER-Net: Trustworthy Medical Image Segmentation with Uncertainty Propagation in Encoder-Decoder Networks
Giuseppina Carannante
Dimah Dera
Nidhal C.Bouaynaya
Hassan M. Fathallah-Shaykh
Ghulam Rasool
UQCV
AAML
OOD
27
6
0
10 Nov 2021
Existence, Stability and Scalability of Orthogonal Convolutional Neural
  Networks
Existence, Stability and Scalability of Orthogonal Convolutional Neural Networks
E. M. Achour
Franccois Malgouyres
Franck Mamalet
16
20
0
12 Aug 2021
Brain Tumor Segmentation using an Ensemble of 3D U-Nets and Overall
  Survival Prediction using Radiomic Features
Brain Tumor Segmentation using an Ensemble of 3D U-Nets and Overall Survival Prediction using Radiomic Features
Xue Feng
Nicholas J. Tustison
C. Meyer
38
224
0
03 Dec 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
268
5,660
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
249
9,134
0
06 Jun 2015
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